Daniela Witten Pořadí knih (chronologicky)

This book provides a comprehensive overview of statistical learning techniques, focusing on concepts and applications rather than theoretical complexities. It covers essential topics such as regression, classification, and resampling methods, making it accessible for beginners. Real-world examples and practical exercises enhance understanding, while the inclusion of R programming helps readers implement the methods discussed. Ideal for students and professionals alike, it serves as a valuable resource for those looking to deepen their knowledge in data analysis and machine learning.

This book presents key modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, and clustering.